Chemical Concentrations in each house
Tianli
2024-07-09
phaletes <- read_excel("../data/New Home Study- SVOCs_University of Toronto_March2024.xlsx", sheet = "Passive Air - PDMS (pg.m-3)",range = "A5:N145")## New names:
## • `` -> `...6`colnames(phaletes)[which(names(phaletes) == "House ID")] <- "House_ID" #change column names
colnames(phaletes)[which(names(phaletes) == "Sample ID")] <- "Sample_ID" #change column names
colnames(phaletes)[which(names(phaletes) == "Period (month)")] <- "Period"Detection Frequency
chemical_columns <- c("DEP", "DPP", "DiBP", "DnBP", "BzBP", "DEHP", "DnOP","DiNP")
calculate_detection_frequency <- function(df, chemical) {
# Calculate the total number of observations for the chemical
total_count <- df %>%
nrow()
# Calculate the number of detected (non-"DL") observations for the chemical
detected_count <- df %>%
filter(!!sym(chemical) != "<DL" & !is.na(!!sym(chemical))) %>% # Filter out "DL" and NA values
nrow() # Count the number of remaining rows
# Calculate the detection frequency as the ratio of detected count to total count
frequency <- detected_count / total_count
# Return a data frame with the chemical name and its detection frequency
data.frame(Chemical = chemical, Detection_Frequency = frequency)
}
detection_frequencies <- bind_rows(lapply(chemical_columns, function(chem) {
calculate_detection_frequency(phaletes, chem)
}))
print(detection_frequencies)## Chemical Detection_Frequency
## 1 DEP 0.9000000
## 2 DPP 0.7857143
## 3 DiBP 0.8357143
## 4 DnBP 0.7857143
## 5 BzBP 0.9214286
## 6 DEHP 0.9142857
## 7 DnOP 0.7928571
## 8 DiNP 0.8000000number of observations per house(including DL)
phaletes_detected <- phaletes[phaletes$Period %in% c(0, 3, 6, 9, 12), ]
observations_per_house <- phaletes_detected %>%
group_by(House_ID) %>%
summarise(count = n())
options(tibble.print_max = Inf, tibble.width = Inf)
print(observations_per_house)## # A tibble: 44 × 2
## House_ID count
## <chr> <int>
## 1 NHAQS-008 1
## 2 NHAQS-009 1
## 3 NHAQS-010 1
## 4 NHAQS-011 1
## 5 NHAQS-012 1
## 6 NHAQS-013 1
## 7 NHAQS-014 2
## 8 NHAQS-015 2
## 9 NHAQS-016 2
## 10 NHAQS-018 2
## 11 NHAQS-019 4
## 12 NHAQS-022 3
## 13 NHAQS-023 2
## 14 NHAQS-028 5
## 15 NHAQS-029 5
## 16 NHAQS-030 5
## 17 NHAQS-031 5
## 18 NHAQS-032 5
## 19 NHAQS-033 1
## 20 NHAQS-034 5
## 21 NHAQS-035 4
## 22 NHAQS-036 5
## 23 NHAQS-037 3
## 24 NHAQS-038 5
## 25 NHAQS-039 4
## 26 NHAQS-040 4
## 27 NHAQS-041 4
## 28 NHAQS-042 4
## 29 NHAQS-043 4
## 30 NHAQS-044 4
## 31 NHAQS-045 4
## 32 NHAQS-046 2
## 33 NHAQS-047 4
## 34 NHAQS-048 3
## 35 NHAQS-049 2
## 36 NHAQS-050 4
## 37 NHAQS-052 3
## 38 NHAQS-053 3
## 39 NHAQS-054 3
## 40 NHAQS-055 3
## 41 NHAQS-056 2
## 42 NHAQS-057 2
## 43 NHAQS-059 2
## 44 NHAQS-060 1number of observations per house(exclude DL)
count_valid_observations <- function(df, chemical) {
df %>%
filter(!!sym(chemical) != "<DL") %>%
group_by(House_ID) %>%
summarise(count = n()) %>%
mutate(Chemical = chemical)
}
# Apply the function to each chemical and bind the results together
observations_per_household_chemical <- bind_rows(lapply(chemical_columns, function(chem) {
count_valid_observations(phaletes_detected, chem)
}))
# Print the result
print(observations_per_household_chemical)## # A tibble: 343 × 3
## House_ID count Chemical
## <chr> <int> <chr>
## 1 NHAQS-008 1 DEP
## 2 NHAQS-009 1 DEP
## 3 NHAQS-010 1 DEP
## 4 NHAQS-011 1 DEP
## 5 NHAQS-012 1 DEP
## 6 NHAQS-013 1 DEP
## 7 NHAQS-014 2 DEP
## 8 NHAQS-015 2 DEP
## 9 NHAQS-016 2 DEP
## 10 NHAQS-018 2 DEP
## 11 NHAQS-019 4 DEP
## 12 NHAQS-022 3 DEP
## 13 NHAQS-023 2 DEP
## 14 NHAQS-028 4 DEP
## 15 NHAQS-029 4 DEP
## 16 NHAQS-030 4 DEP
## 17 NHAQS-031 5 DEP
## 18 NHAQS-032 5 DEP
## 19 NHAQS-033 1 DEP
## 20 NHAQS-034 5 DEP
## 21 NHAQS-035 4 DEP
## 22 NHAQS-036 5 DEP
## 23 NHAQS-037 3 DEP
## 24 NHAQS-038 5 DEP
## 25 NHAQS-039 4 DEP
## 26 NHAQS-040 4 DEP
## 27 NHAQS-041 4 DEP
## 28 NHAQS-042 4 DEP
## 29 NHAQS-043 4 DEP
## 30 NHAQS-044 4 DEP
## 31 NHAQS-045 4 DEP
## 32 NHAQS-046 1 DEP
## 33 NHAQS-047 4 DEP
## 34 NHAQS-048 3 DEP
## 35 NHAQS-049 2 DEP
## 36 NHAQS-050 3 DEP
## 37 NHAQS-052 2 DEP
## 38 NHAQS-053 3 DEP
## 39 NHAQS-054 3 DEP
## 40 NHAQS-055 3 DEP
## 41 NHAQS-056 1 DEP
## 42 NHAQS-057 2 DEP
## 43 NHAQS-059 2 DEP
## 44 NHAQS-060 1 DEP
## 45 NHAQS-008 1 DPP
## 46 NHAQS-009 1 DPP
## 47 NHAQS-010 1 DPP
## 48 NHAQS-011 1 DPP
## 49 NHAQS-012 1 DPP
## 50 NHAQS-013 1 DPP
## 51 NHAQS-014 2 DPP
## 52 NHAQS-015 1 DPP
## 53 NHAQS-016 1 DPP
## 54 NHAQS-018 2 DPP
## 55 NHAQS-019 2 DPP
## 56 NHAQS-022 3 DPP
## 57 NHAQS-023 2 DPP
## 58 NHAQS-028 4 DPP
## 59 NHAQS-029 5 DPP
## 60 NHAQS-030 4 DPP
## 61 NHAQS-031 5 DPP
## 62 NHAQS-032 5 DPP
## 63 NHAQS-034 5 DPP
## 64 NHAQS-035 1 DPP
## 65 NHAQS-036 4 DPP
## 66 NHAQS-037 3 DPP
## 67 NHAQS-038 5 DPP
## 68 NHAQS-039 4 DPP
## 69 NHAQS-040 4 DPP
## 70 NHAQS-041 4 DPP
## 71 NHAQS-042 4 DPP
## 72 NHAQS-043 4 DPP
## 73 NHAQS-044 4 DPP
## 74 NHAQS-045 4 DPP
## 75 NHAQS-046 2 DPP
## 76 NHAQS-047 4 DPP
## 77 NHAQS-048 2 DPP
## 78 NHAQS-049 2 DPP
## 79 NHAQS-050 4 DPP
## 80 NHAQS-052 2 DPP
## 81 NHAQS-053 1 DPP
## 82 NHAQS-054 2 DPP
## 83 NHAQS-055 2 DPP
## 84 NHAQS-060 1 DPP
## 85 NHAQS-008 1 DiBP
## 86 NHAQS-009 1 DiBP
## 87 NHAQS-010 1 DiBP
## 88 NHAQS-011 1 DiBP
## 89 NHAQS-012 1 DiBP
## 90 NHAQS-013 1 DiBP
## 91 NHAQS-014 2 DiBP
## 92 NHAQS-015 2 DiBP
## 93 NHAQS-016 2 DiBP
## 94 NHAQS-018 2 DiBP
## 95 NHAQS-019 4 DiBP
## 96 NHAQS-022 3 DiBP
## 97 NHAQS-023 2 DiBP
## 98 NHAQS-028 1 DiBP
## 99 NHAQS-029 4 DiBP
## 100 NHAQS-030 5 DiBP
## 101 NHAQS-031 4 DiBP
## 102 NHAQS-032 4 DiBP
## 103 NHAQS-033 1 DiBP
## 104 NHAQS-034 5 DiBP
## 105 NHAQS-035 4 DiBP
## 106 NHAQS-036 4 DiBP
## 107 NHAQS-037 3 DiBP
## 108 NHAQS-038 5 DiBP
## 109 NHAQS-039 3 DiBP
## 110 NHAQS-040 3 DiBP
## 111 NHAQS-041 4 DiBP
## 112 NHAQS-042 4 DiBP
## 113 NHAQS-043 2 DiBP
## 114 NHAQS-044 3 DiBP
## 115 NHAQS-045 4 DiBP
## 116 NHAQS-046 2 DiBP
## 117 NHAQS-047 3 DiBP
## 118 NHAQS-048 2 DiBP
## 119 NHAQS-049 2 DiBP
## 120 NHAQS-050 4 DiBP
## 121 NHAQS-052 3 DiBP
## 122 NHAQS-053 3 DiBP
## 123 NHAQS-054 3 DiBP
## 124 NHAQS-055 3 DiBP
## 125 NHAQS-056 2 DiBP
## 126 NHAQS-057 1 DiBP
## 127 NHAQS-059 2 DiBP
## 128 NHAQS-060 1 DiBP
## 129 NHAQS-008 1 DnBP
## 130 NHAQS-009 1 DnBP
## 131 NHAQS-010 1 DnBP
## 132 NHAQS-011 1 DnBP
## 133 NHAQS-012 1 DnBP
## 134 NHAQS-013 1 DnBP
## 135 NHAQS-014 2 DnBP
## 136 NHAQS-015 2 DnBP
## 137 NHAQS-016 2 DnBP
## 138 NHAQS-018 2 DnBP
## 139 NHAQS-019 4 DnBP
## 140 NHAQS-022 2 DnBP
## 141 NHAQS-023 2 DnBP
## 142 NHAQS-028 4 DnBP
## 143 NHAQS-029 5 DnBP
## 144 NHAQS-030 4 DnBP
## 145 NHAQS-031 5 DnBP
## 146 NHAQS-032 4 DnBP
## 147 NHAQS-033 1 DnBP
## 148 NHAQS-034 1 DnBP
## 149 NHAQS-035 4 DnBP
## 150 NHAQS-036 3 DnBP
## 151 NHAQS-037 3 DnBP
## 152 NHAQS-038 2 DnBP
## 153 NHAQS-039 3 DnBP
## 154 NHAQS-040 2 DnBP
## 155 NHAQS-041 3 DnBP
## 156 NHAQS-042 4 DnBP
## 157 NHAQS-043 3 DnBP
## 158 NHAQS-044 4 DnBP
## 159 NHAQS-045 4 DnBP
## 160 NHAQS-046 2 DnBP
## 161 NHAQS-047 2 DnBP
## 162 NHAQS-048 3 DnBP
## 163 NHAQS-049 2 DnBP
## 164 NHAQS-050 3 DnBP
## 165 NHAQS-052 3 DnBP
## 166 NHAQS-053 3 DnBP
## 167 NHAQS-054 3 DnBP
## 168 NHAQS-055 3 DnBP
## 169 NHAQS-056 2 DnBP
## 170 NHAQS-059 2 DnBP
## 171 NHAQS-060 1 DnBP
## 172 NHAQS-008 1 BzBP
## 173 NHAQS-009 1 BzBP
## 174 NHAQS-010 1 BzBP
## 175 NHAQS-011 1 BzBP
## 176 NHAQS-012 1 BzBP
## 177 NHAQS-013 1 BzBP
## 178 NHAQS-014 2 BzBP
## 179 NHAQS-015 2 BzBP
## 180 NHAQS-016 2 BzBP
## 181 NHAQS-018 1 BzBP
## 182 NHAQS-019 4 BzBP
## 183 NHAQS-022 3 BzBP
## 184 NHAQS-023 2 BzBP
## 185 NHAQS-028 5 BzBP
## 186 NHAQS-029 5 BzBP
## 187 NHAQS-030 4 BzBP
## 188 NHAQS-031 5 BzBP
## 189 NHAQS-032 5 BzBP
## 190 NHAQS-033 1 BzBP
## 191 NHAQS-034 5 BzBP
## 192 NHAQS-035 4 BzBP
## 193 NHAQS-036 5 BzBP
## 194 NHAQS-037 3 BzBP
## 195 NHAQS-038 5 BzBP
## 196 NHAQS-039 4 BzBP
## 197 NHAQS-040 3 BzBP
## 198 NHAQS-041 4 BzBP
## 199 NHAQS-042 4 BzBP
## 200 NHAQS-043 4 BzBP
## 201 NHAQS-044 4 BzBP
## 202 NHAQS-045 4 BzBP
## 203 NHAQS-046 2 BzBP
## 204 NHAQS-047 4 BzBP
## 205 NHAQS-048 3 BzBP
## 206 NHAQS-049 2 BzBP
## 207 NHAQS-050 4 BzBP
## 208 NHAQS-052 3 BzBP
## 209 NHAQS-053 3 BzBP
## 210 NHAQS-054 2 BzBP
## 211 NHAQS-055 3 BzBP
## 212 NHAQS-056 2 BzBP
## 213 NHAQS-057 2 BzBP
## 214 NHAQS-059 2 BzBP
## 215 NHAQS-060 1 BzBP
## 216 NHAQS-008 1 DEHP
## 217 NHAQS-009 1 DEHP
## 218 NHAQS-010 1 DEHP
## 219 NHAQS-011 1 DEHP
## 220 NHAQS-012 1 DEHP
## 221 NHAQS-013 1 DEHP
## 222 NHAQS-014 2 DEHP
## 223 NHAQS-015 2 DEHP
## 224 NHAQS-016 2 DEHP
## 225 NHAQS-018 2 DEHP
## 226 NHAQS-019 4 DEHP
## 227 NHAQS-022 3 DEHP
## 228 NHAQS-023 2 DEHP
## 229 NHAQS-028 4 DEHP
## 230 NHAQS-029 5 DEHP
## 231 NHAQS-030 5 DEHP
## 232 NHAQS-031 5 DEHP
## 233 NHAQS-032 5 DEHP
## 234 NHAQS-033 1 DEHP
## 235 NHAQS-034 5 DEHP
## 236 NHAQS-035 3 DEHP
## 237 NHAQS-036 4 DEHP
## 238 NHAQS-037 3 DEHP
## 239 NHAQS-038 5 DEHP
## 240 NHAQS-039 4 DEHP
## 241 NHAQS-040 4 DEHP
## 242 NHAQS-041 4 DEHP
## 243 NHAQS-042 4 DEHP
## 244 NHAQS-043 4 DEHP
## 245 NHAQS-044 4 DEHP
## 246 NHAQS-045 4 DEHP
## 247 NHAQS-046 2 DEHP
## 248 NHAQS-047 4 DEHP
## 249 NHAQS-048 2 DEHP
## 250 NHAQS-049 2 DEHP
## 251 NHAQS-050 4 DEHP
## 252 NHAQS-052 3 DEHP
## 253 NHAQS-053 3 DEHP
## 254 NHAQS-054 2 DEHP
## 255 NHAQS-055 3 DEHP
## 256 NHAQS-056 2 DEHP
## 257 NHAQS-057 2 DEHP
## 258 NHAQS-059 2 DEHP
## 259 NHAQS-060 1 DEHP
## 260 NHAQS-008 1 DnOP
## 261 NHAQS-009 1 DnOP
## 262 NHAQS-010 1 DnOP
## 263 NHAQS-011 1 DnOP
## 264 NHAQS-012 1 DnOP
## 265 NHAQS-013 1 DnOP
## 266 NHAQS-014 2 DnOP
## 267 NHAQS-015 2 DnOP
## 268 NHAQS-016 2 DnOP
## 269 NHAQS-018 2 DnOP
## 270 NHAQS-019 4 DnOP
## 271 NHAQS-022 1 DnOP
## 272 NHAQS-023 1 DnOP
## 273 NHAQS-028 5 DnOP
## 274 NHAQS-029 4 DnOP
## 275 NHAQS-030 4 DnOP
## 276 NHAQS-031 5 DnOP
## 277 NHAQS-032 5 DnOP
## 278 NHAQS-034 4 DnOP
## 279 NHAQS-035 4 DnOP
## 280 NHAQS-036 5 DnOP
## 281 NHAQS-037 3 DnOP
## 282 NHAQS-038 2 DnOP
## 283 NHAQS-039 4 DnOP
## 284 NHAQS-040 3 DnOP
## 285 NHAQS-041 3 DnOP
## 286 NHAQS-042 4 DnOP
## 287 NHAQS-043 4 DnOP
## 288 NHAQS-044 4 DnOP
## 289 NHAQS-045 4 DnOP
## 290 NHAQS-046 2 DnOP
## 291 NHAQS-047 4 DnOP
## 292 NHAQS-049 2 DnOP
## 293 NHAQS-050 3 DnOP
## 294 NHAQS-052 3 DnOP
## 295 NHAQS-053 3 DnOP
## 296 NHAQS-054 2 DnOP
## 297 NHAQS-055 2 DnOP
## 298 NHAQS-056 1 DnOP
## 299 NHAQS-057 1 DnOP
## 300 NHAQS-060 1 DnOP
## 301 NHAQS-008 1 DiNP
## 302 NHAQS-009 1 DiNP
## 303 NHAQS-010 1 DiNP
## 304 NHAQS-011 1 DiNP
## 305 NHAQS-012 1 DiNP
## 306 NHAQS-013 1 DiNP
## 307 NHAQS-014 2 DiNP
## 308 NHAQS-015 1 DiNP
## 309 NHAQS-016 1 DiNP
## 310 NHAQS-018 2 DiNP
## 311 NHAQS-019 3 DiNP
## 312 NHAQS-022 2 DiNP
## 313 NHAQS-023 2 DiNP
## 314 NHAQS-028 5 DiNP
## 315 NHAQS-029 3 DiNP
## 316 NHAQS-030 4 DiNP
## 317 NHAQS-031 4 DiNP
## 318 NHAQS-032 5 DiNP
## 319 NHAQS-034 5 DiNP
## 320 NHAQS-035 3 DiNP
## 321 NHAQS-036 3 DiNP
## 322 NHAQS-037 3 DiNP
## 323 NHAQS-038 5 DiNP
## 324 NHAQS-039 4 DiNP
## 325 NHAQS-040 4 DiNP
## 326 NHAQS-041 4 DiNP
## 327 NHAQS-042 4 DiNP
## 328 NHAQS-043 4 DiNP
## 329 NHAQS-044 4 DiNP
## 330 NHAQS-045 2 DiNP
## 331 NHAQS-046 2 DiNP
## 332 NHAQS-047 4 DiNP
## 333 NHAQS-048 3 DiNP
## 334 NHAQS-049 2 DiNP
## 335 NHAQS-050 3 DiNP
## 336 NHAQS-052 3 DiNP
## 337 NHAQS-053 3 DiNP
## 338 NHAQS-054 2 DiNP
## 339 NHAQS-055 1 DiNP
## 340 NHAQS-056 1 DiNP
## 341 NHAQS-057 1 DiNP
## 342 NHAQS-059 1 DiNP
## 343 NHAQS-060 1 DiNPThe Line Plots of all houses and only complete houses
phaletes_filled <- phaletes_detected %>%
mutate(
DEP = ifelse(DEP == "<DL", 50, as.numeric(DEP)),
DPP = ifelse(DPP == "<DL", 101, as.numeric(DPP)),
DiBP = ifelse(DiBP == "<DL", 80, as.numeric(DiBP)),
DnBP = ifelse(DnBP == "<DL", 103, as.numeric(DPP)),
BzBP = ifelse(BzBP == "<DL", 87, as.numeric(BzBP)),
DEHP = ifelse(DEHP == "<DL", 75, as.numeric(DEHP)),
DnOP = ifelse(DnOP == "<DL", 69, as.numeric(DnOP)),
DiNP = ifelse(DiNP == "<DL", 102, as.numeric(DiNP))
) %>%
mutate(Period = as.numeric(as.character(Period))) %>%
arrange(House_ID)## Warning: There were 7 warnings in `mutate()`.
## The first warning was:
## ℹ In argument: `DEP = ifelse(DEP == "<DL", 50, as.numeric(DEP))`.
## Caused by warning in `ifelse()`:
## ! NAs introduced by coercion
## ℹ Run `dplyr::last_dplyr_warnings()` to see the 6 remaining warnings.complete_houses <- phaletes_filled %>%
group_by(House_ID) %>%
filter(n_distinct(Period) == 5) %>%
ungroup()###DEP
#Line Plot for DEP
phaletes_filled %>%
filter(Period %in% c(0, 3, 6, 9, 12)) %>%
select(House_ID, Period, DEP) %>%
ggplot(aes(x = Period, y = DEP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DEP") +
theme_minimal()
# Line plot for DEP (complete case only)
complete_houses %>%
select(House_ID, Period, DEP) %>%
ggplot(aes(x = Period, y = DEP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() + # Optionally add points for better visualization
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DEP for complete houses") +
theme_minimal()
DPP
phaletes_filled %>%
filter(Period %in% c(0, 3, 6, 9, 12)) %>%
select(House_ID, Period, DPP) %>%
ggplot(aes(x = Period, y = DPP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DPP") +
theme_minimal()
complete_houses %>%
select(House_ID, Period, DPP) %>%
ggplot(aes(x = Period, y = DPP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() + # Optionally add points for better visualization
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DPP for complete houses") +
theme_minimal()
DiBP
phaletes_filled %>%
filter(Period %in% c(0, 3, 6, 9, 12)) %>%
select(House_ID, Period, DiBP) %>%
ggplot(aes(x = Period, y = DiBP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DiBP") +
theme_minimal()
complete_houses %>%
select(House_ID, Period, DiBP) %>%
ggplot(aes(x = Period, y = DiBP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() + # Optionally add points for better visualization
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DiBP for complete houses") +
theme_minimal()
DnBP
phaletes_filled %>%
filter(Period %in% c(0, 3, 6, 9, 12)) %>%
select(House_ID, Period, DnBP) %>%
ggplot(aes(x = Period, y = DnBP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DnBP") +
theme_minimal()
complete_houses %>%
select(House_ID, Period, DnBP) %>%
ggplot(aes(x = Period, y = DnBP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() + # Optionally add points for better visualization
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DnBP for complete houses") +
theme_minimal()
BzBP
phaletes_filled %>%
filter(Period %in% c(0, 3, 6, 9, 12)) %>%
select(House_ID, Period, BzBP) %>%
ggplot(aes(x = Period, y = BzBP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of BzBP") +
theme_minimal()
complete_houses %>%
select(House_ID, Period, BzBP) %>%
ggplot(aes(x = Period, y = BzBP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of BzBP for complete house") +
theme_minimal()
DEHP
phaletes_filled %>%
filter(Period %in% c(0, 3, 6, 9, 12)) %>%
select(House_ID, Period, DEHP) %>%
ggplot(aes(x = Period, y = DEHP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DEHP") +
theme_minimal()
complete_houses %>%
select(House_ID, Period, DEHP) %>%
ggplot(aes(x = Period, y = DEHP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DEHP for complete house") +
theme_minimal()
### DnOP
phaletes_filled %>%
filter(Period %in% c(0, 3, 6, 9, 12)) %>%
select(House_ID, Period, DnOP) %>%
ggplot(aes(x = Period, y = DnOP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DnOP") +
theme_minimal()
complete_houses %>%
select(House_ID, Period, DnOP) %>%
ggplot(aes(x = Period, y = DnOP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DnOP for complete house") +
theme_minimal()
DiNP
phaletes_filled %>%
filter(Period %in% c(0, 3, 6, 9, 12)) %>%
select(House_ID, Period, DiNP) %>%
ggplot(aes(x = Period, y = DiNP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DiNP") +
theme_minimal()
complete_houses %>%
select(House_ID, Period, DiNP) %>%
ggplot(aes(x = Period, y = DiNP, group = House_ID, color = House_ID)) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = c(0, 3, 6, 9, 12)) +
ylab("Concentration (pg/m3)") +
xlab("Period (months)") +
ggtitle("Concentration of DiNP for complete house") +
theme_minimal()